This invention concerns an energy-based process for the detection of signals drowned in noise.
Detection tools for a signal for which there is an available model are widely available in the literature, the best known methods being based on the adapted filter concept and, more generally, on the signal processing decision theory (P. Y. ARQUES, Collection Technique et Scientifique des Telecommunications, MASSON). These techniques are used to generate consistent and non-consistent receivers in digital communications (Principle of Coherent Communication A. J. VITERBI, MacGraw-Hill).
However this invention is applicable to the case in which there is no model that can be used for direct application of detection theory. We assume that we are in the presence of background noise, in which an "anomaly" occurs from time to time that, depending on the context, may represent a signal that it would be desirable to detect.
There are many examples in the literature of detection of a "useful" signal in noise, concerning speech detection. Due to its large variability, the speech signal cannot be easily and efficiently modelled and one of the most natural means of detecting it is to perform energy thresholding.
Thus a great deal of research is being carded out at the present time about the instantaneous amplitude with reference to an experimentally determined threshold (Speech-noise discrimination and its applications V. PETIT, F. DUMONT THOMSON-CSF Technical Review--Vol. 12--No. 4--December 1980), or by empirical energy thresholding ("Suppression of Acoustic Noise in Speech Using Spectral Subtraction", S. F. BOLL, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. ASSP-27, No. 2, April 1979), or on the total signal energy during a time slice of duration T, by still experimentally thresholding this energy using, for example, local histograms ("Probleme de detection des frontieres de mots en presence de bruits additifs", P. WACRENIER, Memoire de D.E.A. de l'universite de PARIS-SUD, Centre d'ORSAY--Problem of detecting word boundaries in the presence of additive noise, P. WACRENIER, University of Paris-South, Orsay Center, further studies thesis). Other techniques are presented in "A Study of Endpoint Detection Algorithms in Adverse Conditions: Incidence on a DTW and HMM Recognizer", J. C. JUNQUA, B. REAVES, B. MAK EUROSPEECH 1991.
Heuristics is used widely m all these methods, and few powerful theoretical tools are used.
We should also mention work presented in "Evaluation of Linear and Non-Linear Spectral Subtraction Methods for Enhancing Noisy Speech", A. LE FLOC'H, R. SALAMI, B. MOUY and J-P. ADOUL, Proceedings of "Speech Processing in Adverse Conditions", ESCA WORKSHOP, CANNES-MANDELIEU, 10-13 Nov. 1992, in which all energy exceeding a given experimental threshold is considered to reveal the presence of a useful signal, and all energy below this threshold is considered to be energy due to noise alone when the normal distance (absolute value of the difference) separating them is below a threshold that is also experimental. However in this document written by the Le Floc'h et al, the authors work on the concept of a distance between energies, but the distance used is a single absolute value of the difference of the energies and their work makes considerable use of heuristics.